DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Storage module in claim 11 corresponding to a computer readable storage medium.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 10 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the are directed to a computer readable storage medium per se which is broad enough to encompass a transitory signal which is not one of the statutory categories of invention. See MPEP 2106.03 section I
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 5 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Re claim 5 the claim language of “application of a statistical filter to remove outliers” is applied twice it is unclear if this language is a separate application of a statistical filter or merely redundant claim language. Applicant should amend the claims to remove the language or differentiate between the previous recitation
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1,3,4, 9-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over ANDRÉ LUIS CARVALHO MENDES et al BR 102019004750 A2, in view of Kurabayashi US 20190311471 A1 in further view of Dumm US 20210045361 A1
Re claim 1 Mendes discloses
A method for predicting body mass of herd animal, comprising the steps of: - collecting data from the livestock environment (see abstract note that images of lives stock are collected), including:
capturing and storing images of the livestock environment, wherein the images are RGB-D (see paragraph 48 note that RGB D cameras are used ) images of the top view of the animal (See paragraph 48 and figure 2 and 3 note a overhead view is used) ;
weighing the animal individually (see paragraph 49 note that the animal may be weighed);
detecting and selecting the animal, including (see paragraph 48 “ Figure 2 shows the three-dimensional reconstruction of the animal's body with a camera positioned above the back” the examiner notes that the three dimensional reconstruction represents an identification of the animal:
extracting RGB-D depth images (see paragraph 48 note that RGB D cameras are used perform analysis);
identifying and separating the animal from other elements included in the RGB-D depth image extracted (see paragraph 48 “ Figure 2 shows the three-dimensional reconstruction of the animal's body with a camera positioned above the back” the examiner notes that the three dimensional reconstruction represents an identification of the animal);
- determining geometric characteristics of each RGB-D depth image (see figure 48 note that RGB depth images are used) including the top view of the animal (See paragraph 48 and figure 2 and 3 note a overhead view is used); wherein geometric characteristics include distance between points, area and volume (see paragraph 50 pre-processing, carried out by the embedded software (item 5) aims to remove unwanted data and search the images for measurements of interest, such as volume, areas and distances between points of interest, characterizing the animal's biometric profile, see also paragraph 69 and 70 note that various measurements are chosen from the images);
- obtaining the prediction of body mass of herd (See paragraph 50 the biometry and weighing data (when available) are used by the animal performance software, (item 10), which determines the body weight and growth rate of the animals. note that body weight of the animals i.e. herd is estimated).
Mendes does not disclose
Capturing video images
wherein each RGB-D depth image extracted from the video consists of points that are represented by Cartesian coordinates,
and wherein the points of the RGB-D depth image are associated with the colors of the RGB standard;
and forming a color map for each RGB-D depth image;
Kurabayashi US 20190311471 discloses
wherein each RGB-D (see paragraph 69) depth image consists of points that are represented by Cartesian coordinates (see paragraph 74 note that the depth is represented by a point cloud with x,y,z coordinates i.e cartesian coordinates),
and wherein the points of the RGB-D depth image are associated with the colors (see paragraph 74 note that ) of the RGB standard (see paragraph 69 note that an RGB depth camera is used, ie. using rgb colors); and forming a color map for each RGB-D depth image (see paragraph 74 note that the colored point cloud corresponds to the color map);
The examiner notes that Mendes describes using RGB-D images but does not clearly articulate how these images are represented. One of ordinary skill in the art could have easily substituted the RGB-D images represented using the colorized point cloud of Kuranayashi and the results would have been the same and therefore predictable. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Kurabayashi and Mendes
Kurabayashi and Mendes do not expressly disclose captured images are video images of livestock
Dumm discloses captured images are video images of livestock (see paragraph 34 “Where the photographic data comprises a video, the system may capture several representative still images for each animal from the video for use in calculating an estimated weight” The examiner note that video may be used and representative images may be extracted from the video.). The examiner notes that Drumm discloses that video and photographs may be used interchangeable (see paragraph 32-34). One of ordinary skill int the art could have easily substituted images extracted from video for the images used in the combination of Kurabayashi and Mendes and the invention would operate the same and would therefore be predictable. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Kurabayashi and Mendes with Dumm.
Re claim 3 Mendes further discloses the captured images are RGB-D videos of the animal's back. (see paragraph 48 “ Figure 2 shows the three-dimensional reconstruction of the animal's body with a camera positioned above the back” the examiner notes that the three dimensional reconstruction represents an identification of the animal); Dumm further discloses captured images are video images of livestock (see paragraph 34 “Where the photographic data comprises a video, the system may capture several representative still images for each animal from the video for use in calculating an estimated weight” The examiner note that video may be used and representative images may be extracted from the video.).
Re claim 4 Kurbayashi further discloses n that each RGB-D depth image associated with the color map forms a file comprising the colorized digital image and a cloud of points. (see paragraph 74 note that the colored point cloud corresponds to the color map and comprises a colorized image mapped to a cloud of points this could be considered a file);
Re claim 9 Mendes discloses the step of obtaining the prediction of body mass of herd comprises performing computer modeling using machine learning techniques. (see paragraph 60 and 61 “the present invention employs learning in four models, as shown in Figure 1: learning to obtain automatic measurements based on in vivo images (item 5); learning for image performance prediction software for animals (item 10)” note that machine learning is used to perform the measurements)
Re claim 10 Mendes Kurabayashi and Dumm disclose the features of claim 1 Mendes further does not disclose A computer-readable storage media, comprising a set of instructions that, when executed by a processor, carries out the method for predicting body mass of herd animal. Dumm discloses A computer-readable storage media, comprising a set of instructions that, when executed by a processor, carries out the method for predicting body mass of herd animal. (see paragraph 45 and 46 and 59 the examiner notes the computer readable medium including instructions for carrying out the method). The motivation to combine is to implement the method with a computer (See paragraph 45). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Mendes Kurabayashi and Dumm to reach the aforementioned advantage.
Re claim 11 Mendes Kurabayashi and Dumm disclose the features of claim 1 and at least one RGB-D capture set, including at least one RGB-D imaging sensor (see paragraph 48 note that RGB d cameras may be used) Mendes further does not disclose; at least one storage module; and at least one remote monitoring module; wherein the storage module stores a set of instructions that, when executed by a processor, carries out the method for predicting body mass of herd animal Dumm discloses at least one storage module; and at least one remote monitoring module; ( see paragraph 87 “another instance, the data can be stored in a remotely located server and/or database” ) wherein the storage module stores a set of instructions that, when executed by a processor, carries out the method for predicting body mass of herd animal (see paragraph 45 and 46 and 59 the examiner notes the computer readable medium including instructions for carrying out the method ). The motivation to combine is to implement the method with a computer (See paragraph 45). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Mendes Kurabayashi and Dumm to reach the aforementioned advantage.
Re claim 12 Mendes further discloses the at least one RGB-D capture set is installed in the livestock environment (see paragraph 48 note the RGBd camera may capture images of livestock).
Claim(s) 2, 13 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over ANDRÉ LUIS CARVALHO MENDES et al BR 102019004750 A2, in view of Kurabayashi US 20190311471 A1 in further view of Dumm US 20210045361 A1 and Spicola US 2014/0140582
Re claim 2 Mendes Kurabayashi and Dumm disclose all the elements of claim 1. They do not expressly disclose wherein the livestock environment includes any of an individual containment chute, a stall, a paddock, a passage area or a handling area. Spicola discloses wherein the livestock environment includes any of an individual containment chute (see paragraph 57 note that a image may be captured in a shoot see also paragraph 50), a stall, a paddock, a passage area or a handling area. The motivation to combine is the chute systems described herein can permit effective and accurate animal characteristic detection (e.g., estimation or prediction) in a manner that is less expensive and/or more efficient than certain other chute systems. (see paragraph 50). One of ordinary skill in the art could have easily captured images of animal in a chute to reach the aforementioned advantage. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Mendes Kurabayashi and Dumm with Spicola to reach the aforementioned advantage.
Re claim 13 Mendes Kurabayashi and Dumm disclose all the elements of claim 1. They do not expressly disclose wherein the livestock environment includes any of an individual containment chute, a stall, a paddock, a passage area or a handling area. Spicola discloses wherein the livestock environment includes any of an individual containment chute (see paragraph 57 note that a image may be captured in a shoot see also paragraph 50), a stall, a paddock, a passage area or a handling area. The motivation to combine is the chute systems described herein can permit effective and accurate animal characteristic detection (e.g., estimation or prediction) in a manner that is less expensive and/or more efficient than certain other chute systems. (see paragraph 50). One of ordinary skill in the art could have easily captured images of animal in a chute to reach the aforementioned advantage. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Mendes Kurabayashi and Dumm with Spicola to reach the aforementioned advantage.
Re claim 14 Mendes further discloses the at least one RGB-D capture set is installed in the livestock environment (see paragraph 48 note the RGBd camera may capture images of livestock).. Mendes does expressly disclose a camera installed upper part of the livestock environment. Spicola further discloses a camera installed upper part of the livestock environment (see paragraph 57 note that the camera may be installed at the top of the Chute to get a top view of the animal see paragraph 57) The motivation to combine is the chute systems described herein can permit effective and accurate animal characteristic detection (e.g., estimation or prediction) in a manner that is less expensive and/or more efficient than certain other chute systems. (see paragraph 50). One of ordinary skill in the art could have easily captured images of animal with a camera at the top of a chute system to reach the aforementioned advantage. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Mendes Kurabayashi and Dumm with Spicola to reach the aforementioned advantage.
Allowable Subject Matter
Claim 6-8 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Claim 5 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Cited Art
The following is a listing of prior art considered relevant but not applied in a rejection above:
BENJAMIN US 20230276773 A1 discloses “The disclosure provides systems and methods for automatically and noninvasively analyzing livestock health, wherein to determine at least one of a body composition indicator or a pose indicator based on the data acquired from the camera; store the body composition indicator or pose indicator in a data record associated with the animal of interest; and provide the body composition indicator or pose indicator to a neural network trained to predict an animal outcome for animals of a similar species to the animal of interest.” (see abstract)
ROY US 20210233235 A1 discloses There is described a scale for determining weight of one or more organisms contained in a sample. The scale generally has: a camera having a field of view orientable towards the sample and being configured for acquiring an image of the one or more organisms of the sample; a controller having a memory and a processor configured to perform the steps of: accessing the acquired image; using an organism detection engine being stored on the memory and being trained, detecting one or more organism representations in one or more corresponding portions of the accessed image and generating detection data concerning the one or more detected organism representations; and using an organism weight determination engine being stored on the memory and being trained, determining weight data concerning weight associated to the one or more detected organism representations based on the detection data.( see abstract)
Fournier US 20200225076 A1 discloses In one embodiment, a method executed by a computing system, comprising: receiving pixel samples from three-dimensional (3D) data corresponding to one or more images comprising one or more animals; fitting curves for the received pixel samples; deriving parameters from the curves; determining measurements based on variations in the parameters; and estimating a weight of the one or more animals by applying one or more regression algorithms to the measurements.
BAEK US 20230301279 A1 discloses The objective of the present invention is to provide a poultry weight measurement and weight estimation system, which can estimate weight by considering the unique size of each poultry individual and does not interrupt the transit of poultry. To accomplish the objective, the poultry weight measurement and weight estimation system according to the present invention can comprise: a rotary part which is connected to a motor and rotates and which has a wire wound thereon or unwound therefrom; a measurement unit which is connected to the wire and on which poultry can be placed; a scale unit for measuring the weight of poultry placed on the measurement unit; a camera unit for capturing an image of the top of the measurement unit; and a control unit which controls the motor so that the wire is wound on or unwound from the rotary part, and thus adjusts ascending and descending of the measurement unit, which receives information about the weight measured by the scale unit and information about the image captured by the camera to calculate the per-pixel weight of the poultry on the inner side of the measurement unit, and which estimates the per-pixel weight of the poultry on the outer side of the measurement unit on the basis of the calculation result.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN T MOTSINGER whose telephone number is (571)270-1237. The examiner can normally be reached 9AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chineyere Wills-Burns can be reached at (571) 272-9752. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SEAN T MOTSINGER/Primary Examiner, Art Unit 2673